The Most Ambitious Artificial Intelligence Project In The World Has Been Operating In Near Secrecy For 30 Years

"We've been keeping a very low profile, mostly intentionally,"
said Doug Lenat, president and CEO of Cycorp. "No outside investments, no
debts. We don't write very many articles or go to conferences,
but for the first time, we're close to having this be applicable
enough that we want to talk to you."

IBM's Watson and Apple's Siri
stirred up a hunger and awareness throughout the U.S. for
something like a Star Trek computer that really worked — an
artificially intelligent system that could receive instructions
in plain, spoken language, make the appropriate inferences, and
carry out its instructions without needing to have millions and
millions of subroutines hard-coded into it.

Cycorp charged itself with
figuring out the
tens of millions of pieces of data we rely on as humans — the
knowledge that helps us understand the world — and
to represent them
in a formal way that machines can use to reason. The company's
been working continuously since 1984 and next month marks its
30th anniversary.

"Many of the people are still
here from 30 years ago — Mary Shepherd and I started [Cycorp] in
August of 1984 and we're both still working on it," Lenat said.
"It's the most important project one could work on, which is why
this is what we're doing. It will amplify human
intelligence."

It's only a slight stretch to
say Cycorp is building a brain out of software, and they're doing
it from scratch.

"Any time you look at any kind
of real life piece of text or utterance that one human wrote or
said to another human, it's filled with analogies, modal logic,
belief, expectation, fear, nested modals, lots of variables and
quantifiers," Lenat said. "Everyone else is looking for a free-lunch
way to finesse that. Shallow chatbots show a veneer of intelligence or
statistical learning from large amounts of data. Amazon and
Netflix recommend books and movies very well without
understanding in any way what they're doing or why someone might
like something.

"It's the difference between
someone who understands what they're doing and someone going
through the motions of performing something."

Cycorp's product, Cyc, isn't
"programmed" in the conventional sense. It's much more accurate
to say it's being "taught." Lenat told us that most
people think of computer programs as "procedural, [like] a
flowchart," but building Cyc is "much more like educating a
child."

"We're using a consistent
language to build a model of the world," he said.

This means Cyc can see "the
white space rather than the black space in what everyone reads
and writes to each other." An author might explicitly choose
certain words and sentences as he's writing, but in between the
sentences are all sorts of things you expect the reader to infer;
Cyc aims to make these inferences.

Consider the sentence, "John
Smith robbed First National Bank and was sentenced to 30 years in
prison." It leaves out the details surrounding his being caught,
arrested, put on trial, and found guilty. A human would never
actually go through all that detail because it's alternately
boring, confusing, or insulting. You can safely assume other
people know what you're talking about. It's like pronoun use —
he, she, it — one assumes people can figure out the referent.
This stuff is very hard for computers to understand and get
right, but Cyc does both.

"If computers were human,"
Lenat told us, "they'd present themselves as autistic,
schizophrenic, or otherwise brittle. It would be unwise or
dangerous for that person to take care of children and cook
meals, but it's on the horizon for home robots. That's like
saying, 'We have an
important job to do, but we're going to hire dogs and cats to do
it.'"

If you consider the world's current and imagined robots,
it's hard to imagine them not benefiting from
Cyc-endowed abilities that grant them a more human-like
understanding of the world.

Just like computers with operating systems, we might one
day install Cyc on a home robot to make it incredibly
knowledgeable and useful to us. And because Cycorp started from zero and
was built up with a knowledge of nearly everything, it could be
used for a wide variety of applications. It's already being used
to teach math to sixth graders.

Cyc can pretend to be a
confused sixth grader, and the user's role is to help the AI
agent understand and learn sixth grade math. There's an emotional
investment, a need to think about it, and so on. Our program of
course understands the math, but is simply listening to what
students say and diagnosing their confusion. It figures out what
behavior can it carry out that would be most useful to help them
understand things. It's a possibility to revolutionize sixth
grade math, but also other grade levels and subjects. There's no
reason couldn't be used in common core curriculum as well.

[Hofstadter] might know
what needs to be done for things to be intelligent, but it has
taken someone, unfortunately me, the decades of time to drag that
mattress out of the road so we can do the
work. It's not done by any means, but it's
useful.